Senior Research Scientist

We seek an exceptional researcher specializing in Machine Learning with particular expertise in areas such as Code-oriented LLMs, Agentic Systems, Reinforcement Learning and Reasoning Models. The ideal candidate will demonstrate a strong track record of publishing in top-tier conferences and journals (e.g., NeurIPS, ICML, ICLR, ACL). We are looking to speak to candidates who are based in Sydney for our hybrid working model. Responsibilities - Conduct cutting-edge research in Machine Learning in areas such as Code LLMs, Reasoning Models, Agentic Systems and Reinforcement Learning - Publish influential research outcomes in top-tier Machine Learning conferences and journals (e.g., NeurIPS, ICML, ICLR, ACL) - Collaborate closely with other Research Scientists and Research Engineers, as well as our Engineering teams to translate cutting-edge research into practical solutions applicable in commercial database products - Mentor intern researchers, fostering a collaborative and productive research environment Qualifications - Ph.D. in Computer Science, Computer Engineering, or a closely related field with a specialization in Machine Learning - Proven track record of impactful research publications in top-tier Machine Learning conferences and journals (e.g., NeurIPS, ICML, ICLR, ACL) - Post-PhD industry experience of applying computer science concepts to large scale software development problems is a plus - Experience in building research prototypes and conducting rigorous empirical studies to validate theoretical models - Excellent technical communication skills, verbal and written, with the ability to collaborate across teams About MongoDB MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the data platform for the AI era, enabling builders to create, transform, and disrupt industries with software. MongoDB’s unified data platform, the most widely available, globally distributed data platform on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud data platform and is available across AWS, Google Cloud, and Microsoft Azure. With offices worldwide and over 67,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software. Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world! MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter. MongoDB is an equal opportunities employer. Requisition ID 1273359257

Ph.D. in Computer Science, Computer Engineering, or a closely related field with a specialization in Machine Learning. Proven track record of impactful research publications in top-tier Machine Learning conferences and journals (e.g., NeurIPS, ICML, ICLR, ACL). Post-PhD industry experience of applying computer science concepts to large scale software development problems is a plus. Experience in building research prototypes and conducting rigorous empirical studies to validate theoretical models. Excellent technical communication skills, verbal and written, with the ability to collaborate across teams.

Conduct cutting-edge research in Machine Learning in areas such as Code LLMs, Reasoning Models, Agentic Systems and Reinforcement Learning. Publish influential research outcomes in top-tier Machine Learning conferences and journals (e.g., NeurIPS, ICML, ICLR, ACL). Collaborate closely with other Research Scientists and Research Engineers, as well as our Engineering teams to translate cutting-edge research into practical solutions applicable in commercial database products. Mentor intern researchers, fostering a collaborative and productive research environment.